K-Means Clustering to Identity Twitter Build Operate Transfer (BOT) on Influential Accounts


  • M. Khairul Anam STMIK Amik Riau
  • Ike Yunia Pasa Universitas Muhammadiyah Purworejo
  • Kartina Diah Kusuma Wardhani Politeknik Caltex Riau
  • Lusiana Efrizoni STMIK Amik Riau
  • Muhammad Bambang Firdaus Universitas Mulawarman




K-Means clustering, Twitter accounts, Build Operate Transfer (BOT), influential accounts


Twitter is a popular social media with hundreds of millions of users, but some are not human. About 48 million accounts are created by Build Operate Transfer (BOT), which represents up to 15% of all accounts. BOTs are created for various purposes, one of which is to post information about news automatically. However, BOTs have also been abused, such as spreading hoaxes or influencing public perception of a topic. The research aimed to determine which Twitter accounts were identified as BOT accounts based on predefined attributes. The research used tweet data from 213 Twitter accounts. The accounts used as test data were accounts that had influence. After that, the data were clustered using k-means using the attributes of retweets + replies count, followers count, account age, friends count, status count, digits count in name, username length, name similarity, name ratio, and likes count. The results show the optimal number of clustering at k = 3 on the Sum of Squared Errors (SSE) evaluation and the Elbow method and the best quality and cluster power at k = 2 on the silhouette coefficient. It shows that the clustered accounts with the highest number of members on each attribute are places for accounts with high BOT scores from several aspects of the BOT score type.


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Author Biographies

M. Khairul Anam, STMIK Amik Riau

Department of Informatics Engineering

Ike Yunia Pasa, Universitas Muhammadiyah Purworejo

Department of Information Technology, Faculty Engineering

Kartina Diah Kusuma Wardhani, Politeknik Caltex Riau

Department of Informatics Engineering

Lusiana Efrizoni, STMIK Amik Riau

Department of Informatics Engineering

Muhammad Bambang Firdaus, Universitas Mulawarman

Department of Informatics, Faculty of Engineering


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